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Sensors 2016, 16(2), 213;

A Wearable Channel Selection-Based Brain-Computer Interface for Motor Imagery Detection

Institute of Electrical and Control Engineering, National Chiao Tung University, Hsinchu 300, Taiwan
Department of Engineering and Maintenance, Chang Gung Memorial Hospital, Kaohsiung 833, Taiwan
Institute of Imaging and Biomedical Photonics, National Chiao Tung University, Tainan 711, Taiwan
Department of Electronics Egineering, National Chiao Tung University, Hsinchu 300, Taiwan
Department of Medical Research, Chi-Mei Medical Center, Tainan 710, Taiwan
These authors contributed equally to this work.
Author to whom correspondence should be addressed.
Academic Editor: Ki H. Chon
Received: 2 December 2015 / Accepted: 2 February 2016 / Published: 6 February 2016
(This article belongs to the Special Issue Smartphone-Based Sensors for Non-Invasive Physiological Monitoring)
Full-Text   |   PDF [3004 KB, uploaded 6 February 2016]   |  


Motor imagery-based brain-computer interface (BCI) is a communication interface between an external machine and the brain. Many kinds of spatial filters are used in BCIs to enhance the electroencephalography (EEG) features related to motor imagery. The approach of channel selection, developed to reserve meaningful EEG channels, is also an important technique for the development of BCIs. However, current BCI systems require a conventional EEG machine and EEG electrodes with conductive gel to acquire multi-channel EEG signals and then transmit these EEG signals to the back-end computer to perform the approach of channel selection. This reduces the convenience of use in daily life and increases the limitations of BCI applications. In order to improve the above issues, a novel wearable channel selection-based brain-computer interface is proposed. Here, retractable comb-shaped active dry electrodes are designed to measure the EEG signals on a hairy site, without conductive gel. By the design of analog CAR spatial filters and the firmware of EEG acquisition module, the function of spatial filters could be performed without any calculation, and channel selection could be performed in the front-end device to improve the practicability of detecting motor imagery in the wearable EEG device directly or in commercial mobile phones or tablets, which may have relatively low system specifications. Finally, the performance of the proposed BCI is investigated, and the experimental results show that the proposed system is a good wearable BCI system prototype. View Full-Text
Keywords: brain-computer interface; motor imagery; channel selection; spatial filter brain-computer interface; motor imagery; channel selection; spatial filter

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Lo, C.-C.; Chien, T.-Y.; Chen, Y.-C.; Tsai, S.-H.; Fang, W.-C.; Lin, B.-S. A Wearable Channel Selection-Based Brain-Computer Interface for Motor Imagery Detection. Sensors 2016, 16, 213.

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